Related papers: The Solar System Notification Alert Processing Sys…
The Asteroid Terrestrial-impact Last Alert System (ATLAS) carries out its primary planetary defense mission by surveying about 13000 deg^2 at least four times per night. The resulting data set is useful for the discovery of variable stars…
We report on the serendipitous observations of Solar System objects imaged during the High cadence Transient Survey (HiTS) 2014 observation campaign. Data from this high cadence, wide field survey was originally analyzed for finding…
Context. The populations of small bodies of the Solar System (asteroids, comets, Kuiper Belt objects) are used to constrain the origin and evolution of the Solar System. Both their orbital distribution and composition distribution are…
The Dark Energy Survey is able to collect image data of an extremely large number of extragalactic objects, and it can be reasonably assumed that many unusual objects of high scientific interest are hidden inside these data. Due to the…
Making an inventory of the Solar System is one of the four pillars that the requirements for the Large Synoptic Survey Telescope (LSST) are built upon. The choice between same-filter nightly pairs or different-filter nightly pairs in the…
We present the design and commissioning of Project Solaris, a global network of autonomous observatories. Solaris is a Polish scientific undertaking aimed at the detection and characterization of circumbinary exoplanets and eclipsing binary…
Most real-world IoT data analysis tasks, such as clustering and anomaly event detection, are unsupervised and highly susceptible to the presence of outliers. In addition to sporadic scattered outliers caused by factors such as faulty sensor…
Solar flares not only pose risks to outer space technologies and astronauts' well being, but also cause disruptions on earth to our hight-tech, interconnected infrastructure our lives highly depend on. While a number of machine-learning…
We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…
We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey…
Astronomical outliers, such as unusual, rare or unknown types of astronomical objects or phenomena, constantly lead to the discovery of genuinely unforeseen knowledge in astronomy. More unpredictable outliers will be uncovered in principle…
Remote-sensing observations of Solar System objects with a space telescope offer a key method of understanding celestial bodies and contributing to planetary formation and evolution theories. The capabilities of Twinkle, a space telescope…
Wireless Sensor Networks (WSNs) have recently attracted greater attention worldwide due to their practicality in monitoring, communicating, and reporting specific physical phenomena. The data collected by WSNs is often inaccurate as a…
In recent years, automatic classifiers of image cutouts (also called "stamps") have shown to be key for fast supernova discovery. The Vera C. Rubin Observatory will distribute about ten million alerts with their respective stamps each…
The vast diversity of planetary systems detected to date is defying our capability of understanding their formation and evolution. Well-defined volume-limited surveys are the best tool at our disposal to tackle the problem, via the…
Despite extensive searches and the relative proximity of solar system objects (SSOS) to Earth, many remain undiscovered and there is still much to learn about their properties and interactions. This work is the first in a series dedicated…
Earth is bombarded by meteors, occasionally by one large enough to cause a significant explosion and possible loss of life. Although the odds of a deadly asteroid strike in the next century are low, the most likely impact is by a relatively…
In this work we apply and expand on a recently introduced outlier detection algorithm that is based on an unsupervised random forest. We use the algorithm to calculate a similarity measure for stellar spectra from the Apache Point…
Outlier detection is a significant area in data mining. It can be either used to pre-process the data prior to an analysis or post the processing phase (before visualization) depending on the effectiveness of the outlier and its importance.…
Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications perform outlier…